1. Field of the Disclosure
This disclosure generally relates to data calibration, and more specifically to post-harvest yield data calibration.
2. Description of the Related Art
Modern GPS-based control systems in machines such as, for example, combine harvesters allow producers to collect crop information (e.g., yield information) at sampled points (e.g., yield data points) while a field is being harvested. The types of information collected differ depending on the make and model of the measuring instrument. Commonly collected information includes instantaneous yield information (e.g. bushels per acre (bu/ac)), location information, moisture levels, and machine and/or implement settings (e.g., rotations per minute, fuel consumption, etc.).
As with many measurement instruments, the accuracy of these measuring instruments vary for a number of reasons (e.g. global positioning system (GPS) drift, damage, temperature fluctuation, etc.). An important component in maintaining accuracy is calibration, which can be defined as the adjustment of a measuring instrument with a known standard. One specific example includes adjusting the levels of an on-board, or otherwise connected, moisture sensor to match a known result from a trusted source, such as, for example, the readings obtained from an external data source such as, for example, a ground based machine.
There is considerable value in a properly calibrated measuring instrument, however, calibration is a process that is not always performed, and calibration problems can intensify as machines progress through a field during a harvest.